System and method for determining copies-per-unit-volume using pcr and flow control of droplets

ABSTRACT

Methods and systems for quantification of a target nucleic acid in a sample are provided. The method includes forming a plurality of discrete sample portions. Each of the plurality of discrete sample portions comprising a portion of the sample, and a reaction mixture. The method further includes amplifying the plurality of discrete sample portions to form a plurality of discrete processed sample portions. At least one discrete processed sample portion containing nucleic acid amplification reaction products. Fluorescence signals are detected from the at least one of the plurality of discrete processed sample portions to determine a presence of the at least one target nucleic acid. The method also includes determining the respective volumes of the plurality of the plurality of discrete processed sample portions, and estimating the number of copies-per-unit-volume of the at least one target nucleic acid in the sample. Estimating the number of copies-per-unit-volume is based on the number of discrete processed sample portions determined to contain the at least one target nucleic acid therein.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of application Ser. No. 14/009,304filed Oct. 1, 2013, and a National Stage entry from PCT Application No.PCT/US2012/031533 filed Mar. 30, 2012, which claims a benefit under 35USC §119(e) from U.S. Provisional Application Nos. 61/470,713, filedApr. 1, 2011, and 61/481,085, filed Apr. 29, 2011; all applications areincorporated herein by reference in their entirety.

BACKGROUND

The present disclosure generally relates to systems and methods forcarrying out digital polymerase chain reaction (dPCR) assays. Thedisclosure further relates to controlling the flow of droplets dispersedin a carrier fluid through a conduit.

Digital Polymerase Chain Reaction (dPCR) is a method that has beendescribed, for example, in U.S. Pat. No. 6,143,496 to Brown et al.Results from dPCR can be used to detect and quantify the concentrationof rare alleles, to provide absolute quantitation of nucleic acidsamples, and to measure low fold-changes in nucleic acid concentration.

dPCR is often performed using apparatus adapted from conventional qPCR,in which replicates are arrayed in a two dimensional array formatincluding m rows by n columns, i.e., an m×n format. PCR cycling andread-out (end-point or real-time) generally occurs within the samearray. A maximum of m×n replicates can be processed in a single batchrun. Generally, increasing the number of replicates increases theaccuracy and reproducibility of dPCR results.

The (m×n) format in most quantitative polymerase chain reaction (qPCR)platforms is designed for sample-by-assay experiments, in which PCRresults need to be addressable for post-run analysis. For dPCR, however,the specific position or well of each PCR result may be immaterial andonly the number of positive and negative replicates per sample may beanalyzed.

The read-out of dPCR, that is, the number of positive reactions and thenumber of negative reactions, is linearly proportional to the templateconcentration, while the read-out of qPCR (signal vs. cycle) isproportional to the log of the template concentration. For this reason,dPCR typically is constrained to a narrow dynamic range of templateinput.

SUMMARY

According to various embodiments, the present teachings provide methodsand systems for quantification of a target nucleic acid in a sample. Themethod includes forming a plurality of discrete sample portions. Each ofthe plurality of discrete sample portions comprising a portion of thesample, and a reaction mixture. The method further includes amplifyingthe plurality of discrete sample portions to form a plurality ofdiscrete processed sample portions. At least one discrete processedsample portion containing nucleic acid amplification reaction products.Fluorescence signals are detected from the at least one of the pluralityof discrete processed sample portions to determine a presence of the atleast one target nucleic acid. The method also includes determining therespective volumes of the plurality of the plurality of discreteprocessed sample portions, and estimating the number ofcopies-per-unit-volume of the at least one target nucleic acid in thesample. Estimating the number of copies-per-unit-volume is based on thenumber of discrete processed sample portions determined to contain theat least one target nucleic acid therein.

In some embodiments, the plurality of discrete sample portions maycomprise sample portions of different sizes or all of the same size.Each of the plurality of discrete sample portions may comprise a volumeof an aqueous reaction medium at least partially surrounded by a mediumthat is at least substantially immiscible with the plurality of discretesample portions. As used herein, sample portions may be referred to asdroplets, sample volumes, or reactions volumes, for example. The mediumthat is substantially immiscible with the plurality of discrete sampleportions may comprise one or more of a mineral oil, a silicone oil, aparaffin oil, a fluorinated fluid, a perfluorinated polyether, and acombination thereof. In some embodiments, the plurality of discretesample portions comprise magnetic beads and the method may furthercomprise magnetically focusing the magnetic beads within a flow streamin a flow cytometer. In some embodiments, the plurality of sampleportions may comprise non-magnetic beads, including porous or hollowbeads, for example. The porous or hollow beads may be spherical orcylindrical. One or more of the plurality of sample portions maycomprise a passive reference dye, a light-scattering enhancing material,q-dots, a protein, a colloidal metal, colloidal gold, a reporter dye, areaction-independent flow marker, or a combination thereof. In someembodiments, one or more sample discrete portions of the plurality ofsample portions comprises a primer pair, a nucleotide probe, and a Taqpolymerase.

In another embodiment, a system for quantification of a target nucleicacid in a sample is provided. The system includes an emulsion apparatusconfigured to form a plurality of discrete sample portions. Each of theplurality of discrete sample portions includes a portion of the sample,and a reaction mixture. The system further includes an amplificationapparatus configured to amplify the plurality of discrete sampleportions to form a plurality of discrete processed sample portions,including at least one discrete processed sample portion containingnucleic acid amplification reaction products. The system also includesexcitation detection apparatus configured to detect fluorescence signalsfrom the at least one of the plurality of discrete processed sampleportions to determine a presence of the at least one target nucleicacid. Furthermore, the system includes a processor configured toestimate the number of copies-per-unit-volume of the at least one targetnucleic acid in the sample based on the number of discrete processedsample portions determined to contain the at least one target nucleicacid therein.

BRIEF DESCRIPTION OF THE DRAWINGS

A better understanding of the features and advantages of the presentdisclosure will be obtained by reference to the accompanying drawings,which are intended to illustrate, not limit, the present teachings.

FIG. 1 is a flow diagram of an exemplary method according to variousembodiments of the present teachings.

FIG. 2 is a flow diagram of another exemplary method according tovarious embodiments of the present teachings.

FIG. 3 is a schematic diagram of an exemplary system and methodaccording to various embodiments of the present teachings.

FIG. 4 is a block diagram of an exemplary system according to variousembodiments of the present teachings.

FIG. 5A depicts a plurality of discrete sample portions according tovarious embodiments of the present teachings.

FIG. 5B depicts a plurality of discrete processed sample portionsaccording to various embodiments of the present teachings.

FIG. 6 illustrates an exemplary optical setup using flow cytometry toanalyze a plurality of discrete sample portions according to variousembodiments of the present teachings.

FIG. 7A illustrates flow data of samples that included no templatecontrol according to various embodiments of the present teachings.

FIG. 7B illustrates flow data of samples including a template controlaccording to various embodiments of the present teachings.

FIGS. 8A and 8B illustrate a three layered emulsion according to variousembodiments of the present teachings.

FIG. 9 illustrates a method of preparing a sample according to variousembodiments of the present teachings.

FIGS. 10-15 illustrate exemplary plots showing a relationship betweenC_(q) and copy number according to various embodiments of the presentteachings.

FIGS. 16-21 illustrate exemplary modeled C_(q) plots versus actual C_(q)plots.

FIGS. 22-33 illustrate exemplary C_(q) distributions according tovarious embodiments of the present teachings.

FIG. 34 illustrates an exemplary histogram for determining PCRefficiency according to various embodiments of the present teachings.

DETAILED DESCRIPTION

The systems and methods described herein provides a dPCR system andmethod that does not rely on the fixed (m×n) format and instead usesdroplet flow control to greatly increases the number of dPCR replicatesthat can be obtained while also obtaining a tally of positive andnegative results useful for dPCR. Unlike fixed format approaches, theaccuracy and precision of the dPCR result can be tuned as desired,simply by varying the observation time and flow rate to obtain therequired number of replicates.

In various embodiments, the methods and systems described herein may beused to detect other biological components of interest. These biologicalcomponents of interest may be any suitable biological target including,but are not limited to, DNA sequences (including cell-free DNA), RNAsequences, genes, oligonucleotides, molecules, proteins, biomarkers,cells (e.g., circulating tumor cells), or any other suitable targetbiomolecule.

Furthermore, in addition to dPCR, the methods and systems in variousembodiments may be used in applications, such as fetal diagnostics, PCR,qPCR, dPCR, allele-specific PCR, asymmetric PCR, ligation-mediated PCR,multiplex dPCR, nested PCR, bridge PCR, genome walking, viral detectionand quantification standards, genotyping, sequencing validation,mutation detection, detection of genetically modified organisms, rareallele detection, and copy number variation.

As used herein, droplets may be referred to as sample portions, samplevolumes, or reactions volumes, for example.

In some embodiments, a flow cytometer, for example, an acoustic flowcytometer can be used to control the flow of aqueous droplets dispersedin a substantially immiscible carrier fluid, through a conduit.

According to various embodiments, analysis of a sample may includepreparing uniform or variously-sized sample portions. The sampleportions are amplified so that the sample portions contain the targetnucleic acid. Amplification may be performed by polymerase chainreactions (PCR) with target concentration near terminal dilution.According to various embodiments, amplification may also be performed byisothermal amplification, thermal convention, infrared mediated thermalcycling, or helicase dependent amplification, for example.

According to various embodiments, detection of a target may be, but isnot limited to, fluorescence detection, detection of positive ornegative ions, pH detection, voltage detection, or current detection,alone or in combination, for example.

The volume of the sample portions may be known. If the sample portionsare different sizes, the volume of the sample portions may need to bedetermined. The positive and negative reactions within the plurality ofsample portions are counted. More particularly, the number of sampleportions that contain successful amplification of the target nucleicacid are counted. The sizes and the positive and negative reactions maybe determined by imaging, for example. The average copy number perreaction is estimated. The estimation may be made using a Poissondistribution. Then, the target copy number per unit volume in thestarting sample is estimated. This exemplary method is generally shownin the flow chart depicted in FIG. 1.

As shown in FIG. 1, the method may comprise forming a plurality ofdiscrete sample portions in step 102. Each of the plurality of adiscrete sample portions may include a portion of the sample, andreaction reagents, such as PCR reagents. The sample may also be diluted.In some embodiments the plurality of discrete sample portions may bereactor droplets. The plurality of discrete sample portions may also beporous beads or magnetic beads, for example. The discrete sampleportions may be a plurality of sizes, a uniform size, or differentpredetermined sizes.

The method may further comprise amplification of the plurality ofdiscrete sample portions to form a plurality of processed sampleportions in step 104. At least one of the plurality of discreteprocessed sample portions contain nucleic acid amplification reactionproducts. The amplification may be by subjecting the reactor droplets tothermal cycling in various embodiments.

Then, the method may include detecting fluorescence signals from theprocessed sample portions to determine a presence of at least one targetnucleic acid, as in step 106. In other words, the plurality of discreteprocessed sample portions may be determined to be positive or negativefor amplification. According to various embodiments, detection of atarget may be, but is not limited to, fluorescence detection, detectionof positive or negative ions, pH detection, voltage detection, orcurrent detection, alone or in combination, for example.

The method further includes determining the respective volumes of theplurality of discrete processed sample portions in step 108. The volumesmay be determined from imaging the plurality of discrete processedsample portions. In various embodiments, the imagining may be done bypositioning the plurality of discrete sample portions in the field ofview of an imagining apparatus. This may be used where the plurality ofdiscrete sample portions are a plurality of sizes, which may be referredto as a polydisperse emulsion. In other embodiments, the discrete sampleportions may be of a uniform size and the volume may be known. In yetother embodiments, the discrete sample portions may be a known number ofdifferent sizes, which may be referred to as an multi-mono dispersedemulsion. For example, the discrete sample portions may be two differentsizes. In other embodiments, the discrete sample portions may be threedifferent sizes, for example. In this way, by determining which sizeeach of the plurality of discrete sample portions is, the volume may bedetermined.

According to various embodiments, a method is provided to createmonodisperse reverse emulsions using T-junctions, as described forexample, in U.S. Patent Application Publication No. US 2007/0141593 A1to Lee et al., which is incorporated herein in its entirety byreference. There would thus be no need to estimate the size of thediscrete sample portions. Some or all of these workflow steps may beintegrated into a single closed system.

The polydisperse emulsions achieved by the present systems and methodsare relatively easy and cheap to make, and do not require a consumable.Due to the difference in volume of the discrete sample portions volumes,they create approximately 3OM greater dynamic range of sample input fordPCR without sample dilution. Acoustic focusing allows massive dropletthroughput and low shear stress to stabilize the plurality of discretesample portions in a flow. Also, acoustic focusing has flow speedflexibility that allows a significant signal to noise increase byvarying flow speeds. This process allows very high numbers of discretesample portions to be read, increasing the accuracy, precision, anddynamic range of dPCR.

The method may further include estimating the number of target templatecopies-per-unit-volume of the at least one target nucleic acid in thesample based on the number of discrete processed sample portionsdetermined to contain the at least one target nucleic acid there, instep 110. As such, the quantity of the target nucleic acid may bedetermined.

In various embodiments, the method may also comprise averaging theresults to improve accuracy and precision and/or estimating the targetcopy number per unit volume in the starting sample. Such methods mayincrease the dynamic range of dPCR and provides alternative analysismethods.

One exemplary method of this type is depicted in the flow chart shown inFIG. 2. As shown in FIG. 2, the method may first comprise generating aplurality of discrete sample portions. More particularly, generating theplurality of discrete sample portions includes combining reactioncomponents that include sample, assay, and PCR reagents, with asubstantially immiscible continuous phase liquid, to form a mixture. Themixture is emulsified to form the plurality of discrete sample portions.In various embodiments, the plurality of discrete sample portions is anemulsion of reactor droplets dispersed in the continuous phase liquid.

Amplification of the plurality of discrete sample portions may beaccomplished by thermal cycling to form a plurality of discreteprocessed sample portions. The plurality of discrete sample portions maybe flowed through a conduit before amplification. In other embodiments,the plurality of discrete processed sample portions, afteramplification, may be flowed the conduit. The plurality of discreteprocessed sample portions are assessed to determine if the discretesample portions are positive or negative for amplification. The volumesof the processed sample portions are estimated. Then, the number oftarget template copies-per-unit-volume in the sample may be estimated.

FIG. 3 is a schematic diagram of an exemplary system and methodaccording to various embodiments of the present teachings. In a firststep of the method, an emulsion apparatus 20 is provided where anemulsion 22 is prepared comprising a plurality of discrete sampleportions 24. With reference to FIG. 4, an exemplary dPCR system 400 isillustrated, including emulsion apparatus 20 for forming a plurality ofdiscrete sample portions. In some embodiments, the discrete sampleportions 24 may be droplets of an aqueous sample dispersed in asubstantially immiscible carrier 26, for example, in a fluorinatedliquid.

FIG. 5A illustrates target nucleic acids 500 contained within discretesample portions of various sizes. Emulsion 22 is then amplified. In someembodiments, the amplification is accomplished by an amplificationapparatus 402, referring back to FIG. 4, thermally cycling such that thediscrete sample portions containing a target nucleic acid are replicatedwithin the discrete sample portion. The amplification apparatus may be aPCR instrument. In another example, the amplification apparatus may be aserpentine thermal cycler. In some embodiments, after amplifying,emulsion 22 is then moved into and through a conduit 28 in the directionof flow shown by flow arrow 30, in a flow cytometry station 32. Inconduit 28, the discrete sample portions 24 may be separated, forexample, to form a single-file line of sample portions. Within, at anexit of, or adjacent an exit of, conduit 28, an excitation detectionapparatus 34 can be located where each discrete sample portion isilluminated by an excitation source 36 and fluorescence that may resultfrom the illumination may be detected, indicating positive amplificationof the target nucleic acid.

FIG. 5B illustrates discrete sample portions with positive amplification502 as well as discrete sample portions with negative amplification 504.The plurality of discrete sample portions may contain a reference dyeonly, contain no reference dye and no target nucleic acid, or contain areference dye and a target nucleic acid.

Following excitation and detection by an excitation detection apparatus404, with reference again back to FIG. 4, a plot of the results can begenerated as shown graphing the detected target nucleic acid signalagainst the detected reference signal. The excitation and detectionapparatus 404 can comprise one or more of the excitation and detectioncomponents described, for example, in U.S. Patent ApplicationPublication No. US 2007/0141593 A1 to Lee et al., which is incorporatedherein in its entirety by reference.

In an exemplary embodiment, a TAQMAN® fluorescent probes qPCR reactionwith target cDNA is overlayed with a 5-fold higher volume of mineral oilin a 96-well plate. An inverse emulsion may be created in an ultrasonicbath. The plurality of discrete sample portions formed using this methodcomprises sample portions from about 1 fL to about 1 pL in volume. Theplurality of discrete sample portions may be thermally cycled in theplate until a plateau of replicates is produced in the positive discretesample portions. With reference back to FIG. 4, an optical imager 404may be used to image the plurality of discrete sample portions in orderto determine size and volume of the discrete sample portions. Forexample, the discrete sample portions may be analyzed using an opticalcamera, or flow cytometry, to estimate the size (volume) and todetermine positivity. Instead of estimating the copy number per droplet,however, the user determines the droplet volume that delivered a certainfrequency of positivity. For example, one could ask what discrete sampleportion size delivered positive amplification reactions at a 66%frequency. If 1 pL discrete sample portions delivered this frequency,then the initial target concentration would be 1.7×10-12M (1.7M). If 1fL discrete sample portions delivered this frequency, then the initialtarget concentration would be 1.7×10-9 (1.7 nM). In an alternativeembodiment, the discrete sample portions positivity frequency may beplotted by discrete sample portions size. The slope of a portion of theresulting curve may be used to estimate the initial discrete sampleportion concentration.

Furthermore, dPCR system 400 can include one or more processors, such asa processor 408. As such, generating any plots or determining theestimating the number of copies-per-unit-volume of the at least onetarget nucleic acid in the sample based on the number of discreteprocessed sample portions determined to contain the at least one targetnucleic acid therein, according to embodiments of the present teachings,may be calculated by processor 408. Processor 408 can be implementedusing a general or special purpose processing engine such as, forexample, a microprocessor, controller or other control logic. Processor408 may be included in a separate computing system, or in any one ofoptical imager 404, excitation detection apparatus 404, amplificationapparatus 402, or emulsion apparatus 20.

It will be appreciated that, for clarity purposes, the above descriptionhas described embodiments of the invention with reference to differentfunctional units and processors. However, it will be apparent that anysuitable distribution of functionality between different functionalunits, processors or domains may be used without detracting from theinvention. For example, functionality illustrated to be performed byseparate processors or controllers may be performed by the sameprocessor or controller. Hence, references to specific functional unitsare only to be seen as references to suitable means for providing thedescribed functionality, rather than indicative of a strict logical orphysical structure or organization.

Forming Discrete Sample Portions

According to various embodiments, the present teachings provide a systemincluding an emulsion apparatus, and a method that uses the same. Theemulsion apparatus generates a plurality of discrete sample portions.The emulsion apparatus may generate the plurality of discrete sampleportions by various methods, such as shaking, stirring, sonicating,extruding, or shear electowetting, for example. In some embodiments, theemulsion apparatus may be a sonicator, a vortexer, or a plate shaker.Emulsification parameters, such as emulsification method,strength/power, time, oil/surfactant chemistry, viscosity,concentration, aqueous phase composition, and water-to-oil ratio, forexample, may be optimized to produce desired sizes for the discretesample portions. In some embodiments, the discrete sample portions havea diameter of between 10μ, to 150 μm and a volume of between 1 pL to 1nL.

Exemplary systems for methods of preparing and processing emulsions thatmay be used according to the present teachings include those describedin U.S. patent application Ser. No. 12/756,547, filed Apr. 8, 2010, toLau et al. for “System and method for preparing and using bulkemulsion,” which is incorporated herein in its entirety by reference.Exemplary systems for methods of processing and thermally cyclingemulsions that may be used according to the present teachings includethose described in U.S. patent application Ser. No. 12/756,783, filedApr. 8, 2010, to Liu et al. for “System comprising dual-sided thermalcycler and emulsion PCR in a pouch,” which is also incorporated hereinin its entirety by reference.

The method may further comprise diluting the sample to form a dilutedsample and forming the plurality of discrete sample portions from thediluted sample. Dilution may comprise terminally diluting the sample toachieve an average of less than one of the at least one target nucleicacid molecules per sample portion. In some embodiments, the methodfurther comprises: serially diluting different portions of the sample bydifferent respective dilution ratios; dividing each serially dilutedportion into a plurality of aliquots; and processing each of theplurality of aliquots of each of the serially diluted portions.

According to various embodiments, the components of the plurality ofdiscrete sample portions may be provided in a multi-well plate. Formingthe plurality of discrete sample portions may include emulsifying anaqueous sample with a medium that is at least substantially immisciblewith the sample. In some embodiments, the emulsifying may comprisemixing the aqueous sample with the medium that is at least substantiallyimmiscible with the sample in the multi-well plate, sonicating theaqueous sample with the medium that is at least substantially immisciblewith the sample in the multi-well plate, shaking the aqueous sample inthe medium that is at least substantially immiscible with the sample inthe multi-well plate, or stirring the aqueous sample in the medium thatis at least substantially immiscible with the sample in the multi-wellplate. Emulsification to form a plurality of discrete sample portionsmay also take place in the presence of a surfactant, so that the kineticstability of the emulsion increases. Some surfactants which may be used,but are not limited to, are Span80, STF9, ABIL EM90, and DC BY 11-030,for example.

In various embodiments, polydisperse emulsions may be generated.Generally, polydisperse emulsions are less difficult to make, minimallyhandled, can be formed in batches, and greatly increase the dynamicrange of dPCR. Furthermore, a small reaction chambers allow analysiswithout sample dilution that can introduce error. For example, heat,shaking, sonic energy, ultrasonic baths, combinations thereof, and thelike can be used to produce emulsions, for example, to process batchesof emulsions in 96-well, 384-well plates, or cell culture plates withoutthe need for any special consumables to physically touch the samples. Inother embodiments, a plate may be used based on the amplificationapparatus. This greatly reduces the chance of cross-contamination. Inaddition, polydisperse emulsions typically vary in volume from about 1fL to 10 pL, eliminating the need to dilute samples to achieve terminaldilutions. Since forming an emulsion may result in very small discretesample portions, the method may further include removing very smalldroplets that may be problematic to detection or amplification.

In another embodiment, multi-mono dispersed emulsions may be formed. Amulti-mono dispersed emulsion may include two or more sizes of discretesample portions, where the sizes are known or predetermined. Forexample, a multi-mono dispersed emulsion may contain three differentsizes of discrete sample portions that are substantially the same sizeas three different predetermined sizes. Substantially means within+/−10% of the predetermined size. By determining the plurality ofdiscrete sample portions which size of the different predetermined sizeseach discrete sample portion is, the volume of each discrete sampleportion can be determined. Multi-mono dispersed emulsions may vary involume from about 1 fL to 10 pL. In other words, each droplet can bebinned into a predetermined size. In this way, the dynamic range can beincreased and an optical imager may be simplified.

Any of a variety of substantially or totally immiscible fluids can beused as the carrier fluid. By immiscible what is meant is immisciblewith respect to the aqueous sample droplets. The substantially ortotally immiscible fluid can comprise, for example, paraffin oil,mineral oil, silicone oil, a perfluorinated polyether (PFPE), otherfluorinated fluids, fluorinated solvents, combinations thereof, and thelike. Some specific fluids that can be used as a carrier fluids includeGALDEN® HT170 available from Solvay Solexis of West Deptford, N.J.,other GALDEN® HT liquids available from Solvay Solexis, FC-40 availablefrom 3M Company of St. Paul, Minn., and other FLUORINER™ liquidsavailable from 3M Company of St. Paul, Minn.

In some embodiments, forming the plurality of discrete sample portionsmay include diluting a sample to near the single molecule limit, andcombining or mixed the sample with all reagents needed for a PCR. A goodinput quantity of template may comprise the dilution limit where eachaqueous reactor volume contains 1 or 0 target nucleic acid molecules,for example, such that the Poisson parameter, λ, is close to or equalto 1. If desired, in order to determine an optimal dilution, an initialquantification using, for example, a QUBIT® system (available from theQubit Systems Inc., Kingston, Ontario, Canada) may be used. Unlikelower-replicate dPCR embodiments, the system and method of the presentteachings can accommodate a much larger deviation from an ideal λ=1input concentration.

Emulsification and Sampling

In various embodiments, a method to prevent evaporation of the aqueousdroplets in water-in-fluorocarbon emulsions is provided. In this way,errors in sampling an emulsion of a plurality of discrete sampleportions are minimized. Discrete sample portions, in this case aqueousdroplets, are formed by adding hydrocarbon oil into a water-fluorocarbonmixture and agitating the three phases together. As such, afteremulsification the hydrocarbon oil forms a layer covering the aqueousdroplets to prevent evaporation.

Density of aqueous phase is around 1 g/cc. Density of fluorocarbon (FC)fluid is about 1.6-1.8 g/cc. Thus, in water-in-fluorocarbon emulsions,aqueous droplets form a layer on top of FC fluid due to the densitydifference. Without a layer to cover the aqueous droplets, the aqueousdroplets may evaporate during storage. Furthermore, evaporation becomesmore severe if the emulsion is heated, for example, in the thermalcycles of the PCR process. Droplets may shrink or evaporate completely,inhibiting biological reactions inside the droplets and makingpost-amplification droplet sizing difficult.

According to various embodiments, hydrocarbon oil may be layered on topof the layer of aqueous droplets. The density of hydrocarbon oil isabout 0.8 g/cc. Thus, the hydrocarbon oil is immiscible with both waterand fluorocarbon. The hydrocarbon oil layer reduces evaporation of theaqueous droplets. However, if the hydrocarbon oil is added afteremulsification, this extra step increases complexity of the process andtime. Furthermore, if many parallel emulsion vessels (e.g. sealed PCRwells) need to be opened to add hydrocarbon oil, it may increase thechance of cross contamination among vessels.

According to various embodiments, hydrocarbon oil is added into thevessels together with a water-fluorocarbon fluid mixture before theemulsification or agitation. Thus there are three phases existing in thevessel. The FC phase contains the fluorocarbon fluid and a surfactant(fluorosurfactant) to make water-in-fluorocarbon emulsion. In oneexample, the fluorocarbon fluid is HFE7500 (3M), the fluorosurfactant isa block copolymer containing hydrophilic poly(ethylene glycol) (PEG)block and fluorophilic poly (perfluoropropylene ether) (PFPE) block, thehydrocarbon oil is a heavy mineral oil (Sigma-Aldrich 330760), and theaqueous phase includes sodium chloride (NaCl) solution 100 mM indistilled water. The aqueous phase contains water and biologicalreagents. The hydrocarbon (HC) phase contains only neat hydrocarbon oil,but no surfactant. The hydrocarbon oil is agitated together withwater-fluorocarbon fluid mixture. After the agitation the aqueous phaseis broken into small aqueous droplets stabilized by the fluorosurfactantand these aqueous droplets form a layer on top of the fluorocarbonfluid. The hydrocarbon oil forms a layer on top of the aqueous dropletlayer preventing the evaporation of the aqueous droplets.

In one example, the vessel may be a MICROAMP® Optical 96-Well ReactionPlate (Applied Biosystems, 4316813) with MICROAMP® Clear Adhesive Film(Applied Biosystems, 4306311). Tube strips can also be used, e.g.Molecular BioProducts PCR 8-Tube Strips.

Example 1

50 uL HFE7500 with 2 wt % fluorosurfactant, 10 uL NaCl and 40 uL heavymineral oil were added in this order into each well on the plate. Theplate was sealed by the adhesive film. When a tube strip is used, thetubes are sealed with cap strip.

The plate or the tube strip was then shaken by an oscillating mixer(RETSCH® MM301) with appropriate adapters. The operating parameter usedin this example was 15 Hz for 1 min.

After shaking, the plate was unloaded from the mixer and kept in theupright position. A layer formed above the HFE7500. This layer containsthe aqueous droplets stabilized by the fluorosurfactant. A clear mineraloil layer was formed on top the droplet layer, preventing theevaporation of aqueous droplets. This three-layered emulsion assembly ina tube-strip is depicted in FIG. 8A.

The plate or the tube strip with the emulsion sample was thermocycledbetween 95° C. and 60° C. for at least 40 cycles and no significantevaporation was observed. This three-layered assembly in a tube-stripafter thermocycles is depicted in FIG. 8B.

Sampling

According to other embodiments, a method to sample the emulsion forsubsequent analysis of the individual droplets is provided.

As described above, the aqueous droplets form a layer on top of thefluorocarbon fluid and are covered by the mineral oil. For subsequentanalysis of the individual aqueous droplets, it is desirable to sampleonly the aqueous droplets and the fluorocarbon fluid, and to remove themineral oil from the sample. An exemplary method is described below,with reference to FIG. 9.

In step 1, a capillary is inserted into a tube. The bottom end of thecapillary is in the fluorocarbon phase and close to the bottom of thetube. In step 2, the fluorocarbon fluid 902 is withdrawn by applyingnegative pressure inside the capillary. The fluorocarbon fluid 902 goesinto the capillary, followed by the aqueous droplets 904, and then themineral oil 906. Next, the negative pressure is stopped when only asmall amount of mineral oil 906 enters the capillary.

In step 3, the capillary is in the upright position. Because the aqueousdroplets 904 have much lower density than the fluorocarbon fluid 902,they will float up until reaching the top of the fluorocarbon fluid 902.The mineral oil 906 inside the capillary tube forms a “plug” under thefluorocarbon fluid, but it does not float up. Thus the aqueous droplets904 and the mineral oil 906 are separated automatically. Additionally,aqueous droplets 904 may be sorted by size because large aqueousdroplets have much higher rising velocity than smaller aqueous droplets.In some embodiments, a variable amount of backflow can be applied toprevent small droplets from migrating up the capillary.

In step 4, sampling, the system can be backflushed to remove residualdroplets and mineral oil.

Example 2

In this example, the emulsion sample described above in Example 1 isused to test the sampling procedure. The emulsion held in an individualwell on a 96-well PCR plate. The volume of the fluorocarbon fluid (HFE7500) plus that of the aqueous droplet layer is 60 uL. The volume of thehydrocarbon oil (heavy mineral oil) is 40 uL. Thus, the total samplevolume in the well is 100 uL.

A GASTIGHT® syringe (Hamilton #81320) is used together with a syringepump (Nexus 3000) to provide negative and positive pressure. The innerwall of a capillary (I.D. 1 mm, length 10 mm) is coated with hydrophobicfluoropolymer coating. This is to prevent the wetting of aqueousdroplets on the inner wall. An open end of the capillary is connected tothe syringe needle via flexible silicone tubing.

In step 1, the capillary was kept upright and the other open end isinserted into the well containing the 3-layered emulsion assembly. Theposition of this end was inside the fluorocarbon fluid and close to thebottom of the tube, as shown in the attached sketch.

In step 2, the “withdraw” mode of the syringe pump was used to createnegative pressure. The total volume to be withdrawn was set to be 70 uLand volumetric rate is set to 10 uL/min. At the end of this step all thefluorocarbon fluid and all the droplets were collected into thecapillary, and only a small fraction of mineral oil (about 10 uL) wasalso collected. The pump was then stopped and no more oil was collected.

In step 3, the capillary was kept upright for Imin. It was seen thatmajority of the aqueous droplets float to the top of the fluorocarbonfluid, and the bottom section of the fluorocarbon fluid became free ofdroplets. The mineral oil “plug” stayed under the fluorocarbon fluid.

In step 4, the “infuse” mode of the syringe pump was used to applypositive pressure inside the capillary. The volume to be infused was setto be 15 uL and the volumetric rate was 10 uL/min.

The mineral oil was pushed out of the capillary, and some fluorocarbonfluid was also pushed out. At the end of step 4, the sample inside thecapillary contained only aqueous droplets and fluorocarbon fluid. Themineral oil was separated from the sample.

In the embodiments described above, a polydispersedwater-in-fluorocarbon emulsion is created directly inside a common96-well PCR plate covered by a lighter oil without an additional step.Aqueous droplets can are sampled, sorted and analyzed by buoyancywithout flow.

As described, embodiments of these methods reduce the evaporation ofaqueous droplets. Furthermore, the cover oil is added together withaqueous reagents and fluorocarbon fluid before emulsification.Eliminating extra step to open the emulsion vessel to add covering oilafter emulsification is avoided. Moreover, the covering oil can beremoved from the emulsion sample and will not interfere with sampleanalysis.

In other embodiments, the plurality of discrete sample portions mayinclude using non-magnetic beads, magnetic beads, or a combinationthereof may be used in the emulsion mix. In some embodiments, theplurality of sample portions may comprise non-magnetic beads, includingporous or hollow beads, for example. The porous or hollow beads may bespherical or cylindrical. In some embodiments, no beads are used.

Detection of Positive or Negative Amplification

According to various embodiments, flow cytometry (FC) is used to countthe number of droplets exhibiting specific fluorescence signals due to,for example, fluorescently-labeled nucleotide probes or antibody tags.The flow cytometry system can provide a fluid flow of suspended reactordroplets through an analysis region in which an excitation and detectionsystem may be used to serially count the number of droplets with one ormore specific fluorescent emission characteristics. Multi-color FCsystems may be used for labeling or tagging droplets and/or targetmolecules with different markers.

TAQMAN® fluorescent probes, SYBR®, LUX™, or other real-time fluorescencedetection methods may be used. If beads and SYBR® are used, and themethod further comprises a flow cytometry step, SYBR® may subsequentlybe included in the running buffer of a flow cytometer to bind and labelbeads containing dsDNA. If beads and TAQMAN® are used, probes may beattached to the beads following cleavage. In some embodiments, labeledprimers, such as LUX™ primers, may be used to label beads, and themethod may allow multiplexing without a need for using a dye-loadedbuffer in a flow cytometry step.

According to various embodiments, a passive reference or spectatorreference can be used in the method, for example, included in theaqueous amplification reagent mix. For bead-based approaches, thepassive reference may be made to attach to the bead during or after theamplification, for example, prior to breaking the emulsion. In anexemplary embodiment, a biotinylated fluorescent ROX™ dye is used with astreptavidin-terminated bead. For non-bead-based emulsions, awater-soluble dye, such as ROX™ dye, may be used.

The present teachings expand the capabilities of dPCR by greatlyincreasing the number of replicates that may be processed in a giventime period when compared to current dPCR methods. The improvements maybe use available instrumentation and overcome the limitations of currentm×n dPCR configurations. In some embodiments, the present teachingsprovide serial processing using conventional flow cytometry systemsapplied to dPCR. In some embodiments, the system and method processesmicelles containing PCR reactants and dispersed in a substantiallyimmiscible carrier fluid. In some embodiments, magnetic focusing is usedin conjunction with flow cytometry and post-read, downstream collectingand processing of single droplets is enabled.

According to various embodiments, emulsion PCR (emPCR) is used and mayinvolve a massively parallel PCR amplification of nucleic acid samplesin aqueous reactors immersed in a substantially immiscible continuousphase, for example, in a non-soluble oil medium. The method may be used,for example, to prepare poly-disperse collections of reactor droplets orlibraries for analysis.

According to various embodiments, fluorescent-activated cell sorting isused such that, following analysis, various fluid manipulation methodsdivert droplets with specific fluorescence signatures to differentlocations or chambers for enrichment or other further processing.

According to the present teachings, a system and method are provided forusing emulsion PCR with a flow cytometry read-out to provide a digitalPCR answer. Unlike conventional flow cytometry systems and methods thatprocess cells, the “cells” in the present flow cytometer system areinstead individual PCR reactant-containing droplet reactors, some ofwhich may comprise replicates of PCR reactions, also referred to aspositive results.

In various embodiments, following the formation of the discrete sampleportions, the resulting amplification products can be introduced into aflow cytometer. This can be accomplished in any suitable way. Forexample, when beads are used, the emulsion can be broken with detergent,rapid aqueous dilution, or another standard emulsion breaking method. Anaqueous suspension of the beads can then be introduced into a flowcytometer in a manner similar to how cells are typically loaded in aconventional cell manipulating flow cytometer. In some embodiments, forbead and bead-less emulsions, lipids may be included in the emulsionfollowed by aqueous dilution to result in micelle formation, wherein thePCR product may be contained, for example, within a lipid bilayer. Sucha droplet can be referred to as a “PCR cell” that may then be introducedand analyzed in a manner used to introduce and analyze a conventionalbiological cell in a flow cytometer.

Plates of emulsified samples can be bulk thermal cycled using a standardthermal cycler, for example, using any of the many thermal cyclersavailable from Applied Biosystems, LLC of Foster City, Calif., forexample. Furthermore, as used herein, thermal cycling may include usinga thermal cycler, isothermal amplification, thermal convention, infraredmediated thermal cycling, or helicase dependent amplification, forexample. In some embodiments, the chip may be integrated with a built-inheating element.

Amplification may be run to completion to create strong signals for thereporters present in droplets containing a target molecule. In someembodiments, a microfluidic meandering PCR method may be used orisothermal amplification techniques may be used to keep emulsionsintact.

According to various embodiments, the method may comprise subjecting theplurality of discrete sample portions to nucleic acid amplificationconditions for carrying out a polymerase chain reaction, for example,thermal cycling conditions.

In some embodiments, the flow cytometer can be set to detect at leasttwo colors, for example, the passive reference and the indicator dye. Inan example, the flow cytometer may be set up to detect fluorescence froma SYBR® dye and from a FAM™ dye. Using TAQMAN® fluorescent probesavailable from Applied Biosystems, LLC of Foster City, Calif.,multiplexing can also be applied generating more than one probe signal,for example, to generate signals form FAM™, VIC®, and other dyes. Forsimplex reactions, 3 types of “cells” should be distinguishable:unlabeled cells from beads/micelles which were not in contact with thesample-PCR mix, cells labeled with the spectator dye only frombeads/micelles which included PCR mix but no template, and cells labeledwith both dyes, where the bead/micelle was in contact with both the PCRmix and a target template.

A digital read-out may be calculated as follows. Two-dye “cells” are 1(indicating mix+template present), passive dye-only “cells” are 0(indicating mix but no template), and un-dyed “cells” are not used inthe calculation. The number of 0 and 1 “cells” is used to fit thePoisson equation, and estimate the number of template molecules presentin the original diluted sample. From that, the number of templatemolecules present in the original undiluted sample can also beestimated.

According to various embodiments, magnetic beads may be used in theassay. Magnetic forces may be used to break the emulsion. Cylindricalsolenoid fields may be used during flow cytometry to focus beads intothe center of the flow stream, increasing the sensitivity and throughputof the flow system. In some embodiments, focusing may be enabled by anacoustic focusing system as described below. Following analysis,variable magnetic fields can be used to direct particular “cells” to anappropriate reservoir.

In some embodiments, if non-magnetic beads are used in the emulsion, amagnetic passive reference may be included in the PCR mix. For example,iron nanoparticles may be used which are functionalized for aqueoussolubility and covalent attachment to polystyrene beads, silica beads,or other beads. In this way, a magnet can be used to retain beads whichare exposed to the reaction mix (true PCR positives and negatives) whilebeads which were not exposed to the mix during formation may be easilywashed away. Such an approach may also be used to facilitate clean-upfor SOLiD™ library preparation.

By using an acoustic focused flow system, as in some embodiments, amethod is provided that has very high speed and flexibility. Also verylow sheer can help keep the emulsion intact during the reading process,as opposed to higher sheer that might disrupt the emulsion and causeinaccurate results. The present systems and methods can measure up to1,000,000 discrete sample portions per sample, for example, from about1.000 to about 1,000,000 discrete sample portions per sample, from about10,000 to about 1,000,000 discrete sample portions per sample, or fromabout 100,000 to about 1,000,000 discrete sample portions per sample.

Exemplary acoustic flow systems and methods and components thereof thatcan be used in the present systems and methods include those described,for example, in U.S. Published Patent Applications Nos. US 2009/0050573A1 to Ward et al. and US 2009/0178716 A1 to Kaduchak et al., both ofwhich are incorporated herein in their entireties by reference. Otherflow cytometry systems and methods having components that can be used inthe present teachings include those described, for example, in U.S.Published Patent Application No. US 2009/013066 A1 to Oldham and in U.S.Pat. No. 7,280,207 B2 to Oldham et al., both of which are alsoincorporated herein in their entireties by reference.

Fluorescent-Activated Cell Sorting (FACS)

Determining a presence or an absence of the at least one target nucleicacid in each of the plurality of processed sample portions may comprisemeasuring a fluorescence signal. After determining the presence orabsence of the at least one target nucleic acid in each of the pluralityof processed sample portions, fluorescent-activated cell sorting (FACS)may be used to sort the plurality of processed sample portions accordingto the fluorescent signal measured. In some embodiments, the volume ofone or more of the processed sample portions may be estimated bymeasuring a fluorescence signal. The determining a presence or anabsence may comprise introducing each of the plurality of processedsample portions individually into a flow cytometer.

If a FACS platform is used, after flow through the analysis region, abead/micelle can be segregated according to the fluorescent signalsdetected. For example, all positive beads can be shunted, directed, ordiverted to a separate reservoir for collection and subsequentdownstream analysis with other methods, for example, for a sequencingreaction or a sequence detection reaction.

The system and method provide the ability to estimate the dropletvolume, as well as the presence of a reporter for PCR amplification. Forthis purpose, a flow cytometer such as a modified acoustic focusing flowcytometer may be used with an autosampler. The flow system mayautosample from 96- or 384-well plates. Acoustic focusing may be sued toenable excellent focus control and can achieve read speeds of 20.000events per second. The size of a droplet can be measured using any of avariety of properties of the droplet, for example, by measuring laserforward or side scatter properties. In some embodiments, a reference dyemay optionally be added to the aqueous phase, and the signal from thereference dye may be used to estimate droplet volume. Positive andnegative counts are available for each droplet that passes the laserinterrogation zone in the center of the acoustically focused flow. Highthroughput using parallel acoustic focusing streams may be achieved.Sorting positive droplets may be employed as a preparatory method forDNA sequencing.

Non-Flow Cytometry Read-Out Alternatives

In some embodiments, read-out methods after emPCR are used that arealternatives to flow cytometry. For example, emulsion products withbeads can be dispersed on a glass slide, for example, containing a thingel matrix for immobilization. The dispersed, fluorescent beads can beread using a SOLiD™ platform (available from Applied Biosystems. FosterCity, Calif.), a conventional fluorescence microscope, or a COUNTESS™cell counting system available from Invitrogen, Carlsbad, Calif. Thepresence of passive reference-only beads indicates the stochastic limithas been reached, and these beads do not need to be quantified. Countingthe number of positive beads then provides quantitation of the templatemolecules present in the initial mix. Micelles and/or beads may also beread serially using Capillary Electrophoresis systems with polymer (orno polymer), for example, using a polymer specially optimized for suchreactors.

According to various embodiments, a system that uses a manual PCR setupis provided that may use SYBR® or TAQMAN®) assays and standard qPCRSuperMixes. The reactions may be set up in a standard 96-well plateusing typical PCR volumes, for example, from about 5 μL to about 15 μL,covered with approximately 50 μL of oil or fluorinated fluid foremulsion PCR. The plate may be sealed using an adhesive cover. Morecomplicated microfluidic reaction assemblies may also be used.

Dilution and Fluorescent-Activated Cell Sorting (FACS)

The present teachings can achieved a throughput of thousands of sampledroplets per minute. As a result, the dynamic range of an assay may beexpanded and the method can be extended to applications typicallyreserved for qPCR, such as gene expression, genotyping, and miRNAanalysis. The present systems and methods are well suited for smallsample inputs, for example, single cell samples. In some embodiments, afluorescent-activated cell sorting (FACS) system is used and the methodmay comprise collecting and purifying selected post-PCR samples fromother samples, obviating the need for user accessibility to andmanipulation of samples in plate or array formats. For example, allmutant amplicons identified by dPCR may be sorted from wild-typeamplicons, for subsequent sequencing.

In some embodiments, the method involves using FACS before and afteremPCR. Prior to emPCR, the FACS can be used to prepare and isolatesingle cells (or types of cells) for analysis. The single cells can belysed and introduced into the emPCR step for subsequent FC analysis. Asan example, circulating tumor cells, as detected by a fluorescentantibody, may be counted and enriched by FACS. The resulting cancer cellproduct can then be analyzed using the dPCR approach described above,that is, emPCR followed by FC/FACS, which provides an extremely lowlimit of detection for quantifying expression levels in these purifiedcells.

The fraction of beads/micelles containing neither passive reference nortemplate may be large if the emulsion PCR process is not optimized. Witha throughput of 10,000 cells per minute, if 10% of beads/micelles are incontact with the PCR mix, 60,000 usable digital replicate results may beobtained in one hour of flow cytometer time. Moreover, the emPCR+FC ofthe present teachings can produce answers beyond typical dPCR results.For example, the method may be used to simply genotype a sample bymeasuring the ratio of the FAM/ROX cells and the VIC®/ROX™ cells. Insome embodiments, with such a high throughput, a 3-5 log dynamic rangemay be attainable for gene expression or miRNA analysis. Using thisapproach, with 60,000 observations per hour, roughly 1,000-folddifferences in expression of two targets may be measured. For example,21,045 cells of target A vs. 24 cells of target B may be quantified, a1000-fold difference in expression levels measured which is absolute inquantity and independent of PCR efficiency and other differences betweenthe two targets.

Volume Estimation of Discrete Sample Portions

In yet other embodiments of the present teachings, an alternative dataanalysis method for absolute target molecule quantification fromheterogeneously sized dPCR reactions, is provided. The method maycomprise determining absolute target concentrations from reactions ofvarious volumes. The reactions may be created with random sizes,randomly or deliberately. The method is useful in analyzing dPCR datafrom polydisperse emulsions, such as emulsions created with mechanicalor sonic energy.

The method may further comprise comparing the plurality of processedportions to a plurality of standards of known respective volumes, forexample, a plurality of standards of known respective volume thatuniformly sized or that are of different known volumes. The method mayfurther comprise subjecting a plurality of portions of a standard to thesame nucleic acid amplification conditions to form a plurality ofprocessed standards, wherein each of the processed standards are of aknown respective volume, and then comparing the plurality of processedstandards to the plurality of processed sample portions. In someembodiments, the plurality of sample portions have an average of fromabout 0.1 to about 0.8 copy of the target nucleic acid per discreteloaded mixture. The plurality of sample portions may have an averagediameter of from about 0.3 micrometer (μm) to about 600 μm, or anaverage diameter of from about 1.0 μm to about 100 μm, or an averagevolume of from about 0.5 femtoliter (fL) to about 1 microliter (μL), oran average volume of from about 10.0 fL to about 100 nanoliters (nL).

According to various embodiments, the volume of the discrete sampleportions is estimated. The present systems and methods may use anoptical imager for using optical scatter properties, a passive referencedye, optical refraction properties, optical imaging for measurement,optical reflection properties, optical absorbance properties, opticaltransmission properties, a ladder of standard droplet sizes usingdifferent reference dyes, or a combination thereof to estimate discretesample portion volumes. An exemplary optical imager 600 is depicted inFIG. 6 to detect samples in flow cell 602. An optical imager may also becamera configured to take images of the discrete sample portions, forexample.

In an example, discrete sample portions of first, second, and thirdvolumes of different known respective standard sizes may contain first,second, and third respective detectably unique dyes and may beidentified and used to scale the size of the discrete sample portionshaving unknown volume sizes. The systems and methods of the presentteachings may produce discrete sample portion sizes of from about 0.3 μmin diameter up to about 1000 μm in diameter, for example, from about 0.4μm in diameter up to about 300 μm in diameter, from about 0.5 μm indiameter up to about 200 μm in diameter, or from about 1.0 μm indiameter up to about 100 μm in diameter. Discrete sample portion volumesof up to about 1.0 μL in size may be produced and processed according tovarious embodiments. Discrete sample portion volumes based on sphericaldiameters can be estimated, for example, using a conversion chart suchas this one:

Radius diameter volume 0.6 uM 1.2 uM 1 fL e. coli 1.4 uM 2.8 uM 10 fL 3uM 6 uM 100 fL 6 uM 12 uM 1 pL 14 uM 28 uM 10 pL human cell 30 uM 60 uM100 pL 60 uM 120 uM 1 nL 140 uM 280 uM 10 nL 300 uM 600 uM 100 nL 600 uM1200 uM 1 uL

Measuring the size of each of the plurality of processed sample portionsmay comprise analyzing each of the plurality of processed sampleportions, and the analyzing may comprise one or more of measuring oranalyzing an index of refraction, a light scattering property, a forwardlight scattering property, a side light scattering property, an opticalabsorption property, an optical transmission property, a peak height ofan optical signal, a peak width of an optical signal, a fluorescentproperty, a time-of-flight fluorescent property, or a combinationthereof. The method may further comprise estimating what size ofprocessed sample portion provides a specific percentage of processedsample portions of that size that test positive for the presence of oneor more of the at least one target nucleic acid, or estimating what sizeprocessed sample portion of the differently-sized processed sampleportions provides a 50% positivity rate with regard to determining thepresence of one or more of the at least one target nucleic acid.

Estimating Number of Copies-Per-Unit-Volume of Sample

According to yet other embodiments of the present teachings, a methodfor estimating the number of copies-per-unit-volume of at least onetarget nucleic acid in a sample is provided. The method may comprise:forming a plurality of discrete sample portions each comprising aportion of a sample, and a reaction mixture; subjecting each of theplurality of discrete sample portions to nucleic acid amplificationconditions to form a plurality of discrete processed sample portionsincluding at least one discrete processed sample portion containingnucleic acid amplification reaction products; generating and measuringfluorescence signals from at least some of the plurality of discreteprocessed sample portions; analyzing each of the plurality of discreteprocessed sample portions individually to determine a presence or anabsence of one or more of the at least one target nucleic acid in eachof the plurality of discrete processed sample portions based on thefluorescence signals, and to determine the respective volumes of theplurality of discrete reacted mixtures; and estimating the number ofcopies-per-unit-volume of the at least one target nucleic acid in thesample based on (1) the number of discrete processed sample portionsdetermined to contain one or more of the at least one target nucleicacid present therein, and (2) the determined respective volumes. Each ofthe plurality of discrete sample portions may be provided in amulti-well plate and the method may further comprise emulsifying to formthe plurality of discrete sample portions.

In some embodiments, the method further comprises estimating what sizeof processed sample portion provides a specific average number ofcopies-per-unit-volume, or estimating what size processed sample portionof the differently-sized processed sample portions provides an averageof from 0.25 to 0.75 copy-per-processed sample portion.

Bayesian Inference to Concentration Estimation

According to various embodiments, an algorithm may be used forestimating target concentration within a dPCR system with multiplediscrete sample portions sizes and/or multiple sample dilutions and/orlow precision in resolving positive and negative amplificationreactions. Typically, data analysis methods for digital PCR systems arebased on a strict set of assumptions that may not be possible to meet inpractice, or may even be undesirable. For example, typical assumptionsmay be: all dPCR discrete sample portions have identical volume, alldPCR discrete sample portions have identical sample dilution, and thedistinction between positive and negative discrete sample portions canalways be made with very high precision

If any of the above assumptions are violated in a practical system, bydesign and/or due to system imperfections, for example, followingstandard data analysis methods may lead to suboptimal results.

According to various embodiments, methods of data analysis may beutilized that explicitly takes into account that discrete sampleportions have varying/uncertain volumes and concentrations, and accountfor measurements of varying quality. This may be achieved by estimatingthe target concentration through Bayesian inference, although otherstatistical estimation techniques are also appropriate.

Some of the following assumptions may need to be incorporated into themodel statistically linking target concentration to measurements:treating discrete sample portion volumes as constants, specifiedseparately for each discrete sample portion, or treating discrete sampleportions volumes as random variables with known distributions (obtainedby characterizing or calibrating the system), or treating discretesample portion volumes as random variables with known conditionaldistributions, dependent on volume dependent measurements obtained atthe run time, such as discrete sample portion diameter estimate,discrete sample portion area estimate, passive reference intensity, etc.

One assumption may be treating discrete sample portion concentrations asconstants, specified separately for each discrete sample portion, ortreating discrete sample portion concentrations as random variables withknown distributions, obtained by characterizing the system and dilutionpreparation protocol.

Another assumption that may be made is treating end-point intensityreads as random variables with known “positive” and “negative”distributions, obtained by characterizing the measurement system.

A goal of Bayesian inference is to produce posterior probabilitydistribution of target concentration, conditional on all availableinformation and measurements. Such posterior distribution may then beused to derive maximum likelihood estimate, unbiased estimate, and/orconfidence interval for target concentration.

Central to these methods, according to various embodiments, is a scorefunction that depends on both the observed results and a specific valueof the target concentration. The score function conveys information onhow good the agreement between a hypothetical value of the concentrationand the actually observed measurements. In other words, a value of thescore function obtained for certain concentration and certainmeasurements is a measure of the likelihood that these measurementscould arise if the sample under consideration indeed had thisconcentration.

Maximum Likelihood Estimation

In one embodiment, the process of estimating the target concentrationinvolves finding the value of concentration for which, given a set ofmeasurements, the score function attains the maximum value (orappropriately high value; or value appropriately close to maximum). Thissearch for maximum value may be performed by evaluating the scorefunction on a predefined set of candidate solutions and choosing themaximum, a successive approximation method, evaluating the analyticalsolution to the maximization problem, or any number of othermaximization method or combination of methods.

Unbiased Estimation

In another embodiment, the process of estimating the targetconcentration involves finding the weighted average of candidateconcentration values (the candidate values coming from a predefined ordynamically established set of discrete of continuous concentrationvalues), where the values of the score function (obtained for thecandidate concentrations) serve as the weights in the averaging process.This process can be achieved by evaluating the score function for all orsubset of candidate values and directly calculating the weightedaverage; or by evaluating an analytical solution; or by any otherappropriate method.

Confidence Interval

In addition to producing the estimate of the target concentration, aconfidence interval may be generated. The confidence interval is a rangeof target concentration values, delimited by the upper value and lowervalue, calculated from the measurements, such that the likelihood thatthe true target concentration value is outside of this range is small.For example, a 95%-confidence interval is where the model-basedprobability of true target concentration being outside of it is 5%. Theconfidence interval can be established as the range of targetconcentration values for which the score function is above certainthreshold. The threshold may be dynamically calculated. For example, thethreshold may be selected such that the sum (or integral) of scorefunction values exceeding the threshold is greater by a predefinedfactor from the sum (or integral) of score function values below thethreshold. (for example, if the score function is in fact a model-basedlikelihood function and 95%-confidence interval is sought, the thresholdis selected so that the integral of likelihoods above the threshold is95/5 times greater that the integral of likelihoods below thethreshold).

Score Function

In some embodiments, the score function can be: a measure ofprobability; a measure of conditional probability; a measure oflikelihood; a logarithm of probability. The score function may use thefollowing probabilistic model that expresses the conditional probabilityof the positive/negative measurements for individual PCR reactionsconditioned on the target concentration and volumes of the PCRreactions. Alternatively, the score function may be a model-basedconditional probability of fluorescence measurements for individual PCRreactions conditioned on the target concentration and on volumemeasurements for the PCR reactions.

Under the constraint on the total number of droplets, digital PCRsystems with multiple droplet sizes and/or multiple sample dilutions cancarry significant dynamic range advantage over system with equally sizedand diluted droplets. However, such a system may need much differentdata analysis to determine target concentration in the original sample.For example, the system may need to take into account discrete sampleportion volumes and dilutions, dilution information may need to beprovided by the user or is system-specific, or discrete sample portionvolume information may be either provided or estimated at run time basedon a size measurement, passive reference intensity, or features ofreal-time amplification curve, for example.

λ—true target concentration in undiluted sampleN—number of dropletsV_(i)—true volume of droplet iC_(i)—true dilution coefficient of droplet i (what fraction of V_(i) istaken up by the undiluted sample)W_(i)—set of measurements or prior information about volume of droplet iD_(i)—prior information about dilution coefficient of droplet iX_(i)—true number of target molecules in droplet iY_(i)—plus/minus measurement for droplet i

P(V_(i)W_(i)) P(C_(i)D_(i)) P(X_(i)V_(i), C_(i), λ)P(Y_(i)X_(i)) P(Y_(i) = 0X_(i) = 0) = 1 − f_(p)P(X_(i)V_(i), C_(i), λ)${P\left( {{Y_{i}D_{i}},W_{i},\lambda} \right)} = {\overset{\infty}{\int\limits_{0}}{\overset{\infty}{\int\limits_{0}}{\sum\limits_{X_{i} = 0}^{\infty}\; {{P\left( {Y_{i}X_{i}} \right)}{P\left( {{X_{i}V_{i}},C_{i},\lambda} \right)}{P\left( {C_{i}D_{i}} \right)}{P\left( {V_{i}W_{i}} \right)}{C_{i}}{V_{i}}}}}}$${P\left( {{YD},W,\lambda} \right)}{\prod\limits_{i = 1}^{N}\; {P\left( {{Y_{i}D_{i}},W_{i},\lambda} \right)}}$${\hat{\lambda}}_{ML} = {\underset{\lambda}{argmax}{\prod\limits_{i = 1}^{N}\; {P\left( {{Y_{i}D_{i}},W_{i},\lambda} \right)}}}$

Multi-Level Digital PCR

In another embodiment, the number of copies of the target nucleic acidmay be estimated based on real-time measurements and C_(q) values todiscriminate between the number of starting template target nucleic acidcopies. C_(q) values are also referred to as C_(T) values in someexamples. In this way, accuracy and dynamic range of dPCR can beenhanced.

As described in various embodiments above, dPCR is based at least inpart on partitioning the sample into a plurality of discrete sampleportion, which may be viewed as a large number of separate PCR reactors.A positive/negative PCR test is performed on each PCR reactor, wherebyeach individual plus/minus test discriminates between zero startingcopies and nonzero starting copies.

According to this embodiment, a method using C_(q) values from eachreactor is provided to achieve higher dynamic range and accuracy thanwould be possible from simple plus/minus calls.

As described above, a positive/negative data analysis is generallydescribed as determining the number of positive and negative reactions.Then, making the assumption that the number of starting template copiesper well follows Poisson distribution, it can be inferred the mostlikely total number of copies from the number of positive and negativewells.

According to this embodiment, a C_(q)-based dPCR data analysis methodincludes determining a number of negative reactions. For reactions thatshowed amplification, the most likely number of starting template copiesfrom Cq is determined. The relationship between C_(q) and copy numbercan be determined by finding peaks in the C_(q) histogram, withrightmost peak corresponding to 1 copy, as illustrated in FIGS. 10-15.The method further includes determining the most likely total number oftemplate copies by summing up template copy numbers from individualreactors.

Furthermore, for each well the likelihoods of starting copy number 0, 1,2, etc, may be determined instead of making a copy number call. This canbe used to determine a total number of copies more precisely withtighter confidence interval. Moreover, the process of associating C_(q)with copy number may also assume Poisson copy number distribution andlogarithmic spacing between C_(q)s.

As the result of using Cq-based dPCR with the above analysis accordingto embodiments described herein, better accuracy and dynamic range withthe same number of reactors, and the same accuracy and dynamic rangewith lower number of reactors compared to plus/minus-based dPCR may beachieved.

Initial PCR Efficiency Determination from dPCT C_(q) Spectrum

According to another embodiment, a method of measuring PCR efficiency inthe first PCR cycle from the Cq spectrum of a dPCR experiment isprovided. The method includes measuring the fraction of replicate PCRreactions with one copy of starting template that did not amplify in thefirst PCR cycle.

PCR efficiency can be described as the percentage of DNA template thatproduces a copy during a single PCR cycle. PCR efficiency is animportant unknown parameter in downstream analysis of real-timeamplification curves. PCR efficiency can differ between cycles of PCR,generally decreasing with each cycle. During real-time PCR, once theamount of PCR template exceeds the detection level, the fluorescenceintensity can be used to monitor the rate of change of the templateamplicon and thus to infer the efficiency.

However, this approach cannot be used to directly measure the efficiencyat the initial cycles when the fluorescence is below detection level. Itis common to make various assumptions about this initial efficiency,such as assuming 100% initial efficiency, assuming initial efficiency isthe same as later, directly observed efficiency, or to use variousmodels that extrapolate the initial efficiency backward from theobserved efficiency.

According to this embodiment, the method includes using a target nucleicacid template dilution that targets the average number of startingtemplate copies per reaction close to 1. This yields high fraction ofreactions to have precisely one starting copy (assuming aPoisson-distribution across reactions). An amplification curve iscollected for all reactions and C_(q) values are obtained.

The method may establish the number of reactions A that had one startingtarget nucleic acid template copy and that copy was amplified in thefirst PCR cycle, and the number of reactions B that had one startingtarget nucleic acid template copy and that copy was not amplified in thefirst PCR cycle, but did amplify in subsequent PCR cycles.

The cycle-1 efficiency can be then calculated as A/(A+B), where A and Bare determined from the Cq histogram. This is based on identification ofthe histogram peak corresponding to the groups A and B, which isillustrated in FIG. 33.

Furthermore, knowledge of the efficiency at the initial PCR cycle can beused as a reagent research and QC tool. Additionally, this method mayalso enhance our qPCR models possibly leading to improved accuracy ofqPCR data analysis.

Also, as mentioned above, in various embodiments, the methods andsystems described herein may be used to detect other biologicalcomponents of interest. These biological components of interest mayinclude, but are not limited to, cells and circulating tumor cells, forexample. Furthermore, in addition to dPCR, the methods and systems invarious embodiments may be used in applications, such as fetaldiagnostics, multiplex DPCR, viral detection, genotyping, and rareallele detection copy number variation.

All publications, patents, and patent applications mentioned in thisspecification are herein incorporated by reference to the same extent asif each individual publication, patent, or patent application wasspecifically and individually indicated to be incorporated by reference.

While embodiments of the present disclosure have been shown anddescribed herein, it will be obvious to those skilled in the art thatsuch embodiments are provided by way of example only. Numerousvariations, changes, and substitutions will now occur to those skilledin the art without departing from the disclosure. It should beunderstood that various alternatives to the embodiments of thedisclosure described herein may be employed in practicing thedisclosure. It is intended that the following claims define the scope ofthe disclosure and that methods and structures within the scope of theseclaims and their equivalents be covered thereby.

1. A method for quantification of a target nucleic acid in a sample, themethod comprising: forming a plurality of discrete sample portions, eachof the plurality of discrete sample portions comprising a portion of thesample, and a reaction mixture, wherein the plurality of discrete sampleportions comprises discrete sample portions of a plurality of sizes;amplifying the plurality of discrete sample portions to form a pluralityof discrete processed sample portions including at least one discreteprocessed sample portion containing nucleic acid amplification reactionproducts; detecting fluorescence signals from the at least one of theplurality of discrete processed sample portions to determine a presenceof the at least one target nucleic acid; determining the respectivevolumes of the plurality of the plurality of discrete processed sampleportions; and estimating the number of copies-per-unit-volume of the atleast one target nucleic acid in the sample based on the number ofdiscrete processed sample portions determined to contain the at leastone target nucleic acid therein.
 2. The method of claim 1, wherein theplurality of discrete sample portions comprises discrete sample portionsof substantially two different sizes.
 3. The method of claim 1, whereinthe plurality of discrete sample portions comprise discrete sampleportions of substantially a plurality of predetermined sizes.
 4. Themethod of claim 1, wherein each of the plurality of sample portions isat least partially surrounded by a medium that is at least substantiallyimmiscible with the plurality of discrete sample portions.
 5. The methodof claim 4, wherein the medium that is substantially immiscible with theplurality of discrete sample portions comprises at least one selectedfrom the group consisting of: a mineral oil, a silicone oil, a paraffinoil, a fluorinated fluid, a perfluorinated polyether.
 6. The method ofclaim 1, wherein the plurality of discrete sample portions comprisesporous beads.
 7. The method of claim 1, wherein the plurality ofdiscrete sample portions comprises magnetic beads.
 8. The method ofclaim 7, further comprising magnetically focusing the magnetic beadswithin a flow stream in a flow cytometer.
 9. The method of claim 1,wherein determining the respective volumes comprises imaging theplurality of discrete processed sample portions.
 10. A system forquantification of a target nucleic acid in a sample, the systemcomprising: an emulsion apparatus configured to form a plurality ofdiscrete sample portions, each of the plurality of discrete sampleportions comprising a portion of the sample, and a reaction mixture; anamplification apparatus configured to amplify the plurality of discretesample portions to form a plurality of discrete processed sampleportions including at least one discrete processed sample portioncontaining nucleic acid amplification reaction products; an excitationdetection apparatus configured to detect fluorescence signals from theat least one of the plurality of discrete processed sample portions todetermine a presence of the at least one target nucleic acid, whereinthe excitation detection apparatus is further configured to determinethe respective volumes of the plurality of the plurality of discreteprocessed sample portions; and a processor configured to estimate thenumber of copies-per-unit-volume of the at least one target nucleic acidin the sample based on the number of discrete processed sample portionsdetermined to contain the at least one target nucleic acid therein. 11.The system of claim 10, further comprising an optical imager configuredto determine the respective volumes of the plurality of the plurality ofdiscrete processed sample portions.
 12. The system of claim 10, whereinthe emulsion apparatus is configured to form the plurality of discretesample portions of a plurality of sizes.
 13. The system of claim 10,wherein the emulsion apparatus is configured to form the plurality ofdiscrete sample portions of substantially two different sizes.
 14. Thesystem of claim 10, wherein the emulsion apparatus is configured to formthe plurality of discrete sample portions of substantially a pluralityof predetermined sizes.
 15. The system of claim 10, wherein each of theplurality of discrete sample portions is at least partially surroundedby a medium that is at least substantially immiscible with the pluralityof discrete sample portions.
 16. The system of claim 15, wherein themedium that is substantially immiscible with the plurality of sampleportions comprises at least one selected from the group consisting of: amineral oil, a silicone oil, a paraffin oil, a fluorinated fluid, aperfluorinated polyether.
 17. The system of claim 10, wherein theplurality of discrete sample portions comprises porous beads.
 18. Thesystem of claim 10, wherein the plurality of discrete sample portionscomprises magnetic beads.
 19. The system of claim 18, wherein theexcitation detection apparatus includes a flow cytometer configured tomagnetically focus the magnetic beads within a flow stream.
 20. Thesystem of claim 10, wherein determining the respective volumes comprisesimaging the plurality of discrete processed sample portions.